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   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "TQu6OACsn1Y2"
   },
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   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from sklearn.datasets import make_blobs\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "yLDb-YRYn1ZE"
   },
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   "source": [
    "# make 3-class dataset for classification\n",
    "centers = [[-5, 0], [0, 1.5], [5, -1]]\n",
    "X, y = make_blobs(n_samples=1000, centers=centers, random_state=40)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
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    "outputId": "3d208ede-7b1e-424a-b660-6f385c53f038"
   },
   "outputs": [],
   "source": [
    "color = \"rbg\"\n",
    "color = [color[y[i]] for i in range(len(y))]\n",
    "plt.scatter(X[:, 0], X[:, 1], c=color)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "KpNVD2gBn1ZL",
    "outputId": "5074f19b-66f3-4947-b59f-31e24153d661"
   },
   "outputs": [],
   "source": [
    "y"
   ]
  }
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